Automatic Audio Classification by Using Hidden Markov Model
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    Abstract:

    As one of the key methods to extract content semantics and structure from audio, automatic audio classification, especially for a speech and a music, is valuable for content-based audio retrieval, video summary and retrieval, and spoken document retrieval, etc. Because hidden Markov model (HMM) can well model audio signal抯 time statistical properties, a left-right discrete HMM is proposed to classify a speech, a music and their mixed audio. The experimental results show that HMM is excellent for audio classification accuracy is up to 90.28%.

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卢坚,陈毅松,孙正兴,张福炎.基于隐马尔可夫模型的音频自动分类.软件学报,2002,13(8):1593-1597

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  • Received:February 13,2001
  • Revised:May 22,2001
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